Hello everyone,
This is the e-mail I've sent out to various neuroscience mailing lists.
Please spread the word.
Thank you all, for all your work. I hope we can continue our work and
keep bringing our Free/Open Source work to (Neuro)Science. đź‘Ź
-----
Hello everyone,
(Apologies for the cross-posts)
The NeuroFedora team is excited to announce the first release of the
CompNeuro-Fedora operating system for computational neuroscientists.
https://labs.fedoraproject.org/en/comp-neuro/
CompNeuro-Fedora is a Fedora Linux based Free/Open Source operating
system that includes a plethora of tools for computational modelling.
These tools are built from their sources as per the Fedora packaging
guidelines that enforce the current best practices in software
development.
So, all you have to do is:
- download the image,
- install it to disk or a virtual machine (or run it "live"), and
- get to work!
This release of the ISO image is based on the popular GNOME desktop
environment. For computational neuroscience, it includes: Auryn,
Bionetgen, Calc: calcium-calculator, COPASI, GetDP, GENESIS, MOOSE, NEST
simulator, NEURON, PyLEMS, Smoldyn; along with multiple tools used in
analysis: the complete Python science stack: NumPy, SciPy, Matplotlib,
IPython, SymPy, and Pandas, R, Julia, GNU Octave, GNUPlot, Paraview, and
others.
Apart from this set of tools, the NeuroFedora team also provides more
neuroscience software that can be installed from the Fedora
repositories. Additionally, you also have access to the *complete* set
of Free/Open Source software packages available for the Fedora Linux
distribution.
You can read more about the CompNeuro-Fedora release here:
https://neuroblog.fedoraproject.org/2020/04/28/fedora-32-computational-neur…
NeuroFedora is a Free/Open Source volunteer community based initiative
to support the use of Free/Open Source software in Neuroscience. The
team consists wholly of volunteers who spend a few hours a week on this
project. We would love to hear from you, and for you to join us. We,
especially encourage students to join the community to develop their
skills while contributing to NeuroFedora.
You can learn more about NeuroFedora here:
https://neuro.fedoraproject.org
You can get in touch with the community using any of our communication
channels:
https://docs.fedoraproject.org/en-US/neurofedora/communicating/
--
Thanks,
Regards,
Ankur Sinha "FranciscoD" (He / Him / His) | https://fedoraproject.org/wiki/User:Ankursinha
Time zone: Europe/London
---------- Forwarded message ---------
From: Brad Wyble <bwyble(a)gmail.com>
Date: Tue, Apr 21, 2020 at 8:41 AM
Subject: [SPM] Call for applications: Neuromatch Summer Academy Students,
TAs and Mentors
To: <SPM(a)jiscmail.ac.uk>
The pandemic has shut down nearly every summer program in the world at
which students, postdocs and faculty would normally gather to acquire
crucial skills and build networks. We’re building a program to replace
this loss. Our plan is to have a 3-week online course July 13-31 focused on
computational analysis and simulation of neural data with intensive
mentoring by knowledgeable TAs and faculty mentors to help with projects.
Tuition will be relatively minimal (~ 100-200 USD) and also voluntary. TAs
will be paid a stipend for their time because it will be intensive.
Mentorship by faculty will be substantially less work.
Interested in signing up as a potential participant, a TA, or a faculty
mentor? Fill out one of the three forms below. Also, please feel free to
send this out as widely as possible. We’re trying to cast a global net,
especially to people outside of the US and Europe. Tutorials will take
place in parallel tracks in different time zones and in multiple languages
when possible.
Note that the deadline for applications is April 27.
Webpage: https://neuromatch.io/academy/
Form for student applications
https://docs.google.com/forms/d/e/1FAIpQLSen1oyFWIQ38vlBSxUdlWU4AwQ_UYGqQZc…
Form for TA applications
https://docs.google.com/forms/d/e/1FAIpQLSc4aL49WV_dnt7WlXjEwsY8Mb30I2E0VHa…
Form for Mentor Applications
https://docs.google.com/forms/d/e/1FAIpQLSef-slmLcnVT7H-wkM-7wT5ePBh3TVg7UX…
--
Brad Wyble
Associate Professor
Psychology Department
Penn State University
http://wyblelab.com
Hello all
I just had a look at the results of the whenisgood that was passed last week.
There was no slot that suited everyone who responded, so I selected
the one so that most people in the group can make it.
We can have our meeting on 27th April (Monday) at 1800 UTC. I hope
that the attendees find the time/day suitable.
I will be happy to chair the meeting, but if anyone else wants to do
it, they are welcome to do so.
--
Thanks
Regards
Aniket Pradhan
http://home.iiitd.edu.in/~aniket17133/
Aliases: MeWjOr/major
() ascii ribbon campaign - against html e-mail
/\ www.asciiribbon.org - against proprietary attachments
Hi!
I ran into this SPM tutorial. It'll be useful for folks that are looking
to learn how to analyse fMRI data:
https://andysbrainbook.readthedocs.io/en/latest/SPM/SPM_Overview.html
Quoting the introduction:
"This course will show you how to analyze an fMRI dataset from start to finish. We will begin by downloading a sample dataset and inspecting the anatomical and functional images for each subject. We will then preprocess the data, which removes noise and enhances the signal in the images. Once the images have been preprocessed, we will create a model representing what we think the BOLD signal, a measure of neural activity, should look like in our images. During model fitting we compare this model with the signal in different areas of the image. This model fit is a measure of the strength of the signal under different conditions - for example, we can take the difference of the signal between conditions A and B of the experiment to see which condition leads to a larger BOLD response.
Once a model has been created for each subject and the BOLD response has been estimated for each condition, we can do any kind of group analysis we like: Paired t-tests, between-group t-tests, interactions, and so on. The goal of this course is to calculate a simple within-subjects contrast between two conditions, and test whether it is significant across subjects. You will also learn how to create figures showing whole-brain analyses, similar to what you see published in the neuroimaging journals, and how to do a region of interest (ROI) analysis.
This course is designed to build your confidence in working with fMRI data, increase your fluency with the basic terms of fMRI analysis, and help you make educated choices during each step. Some chapters have exercises to help you practice what you’ve learned and to prepare you for the next chapter. Once you have mastered the fundamentals of this course, you will be able to apply them to other datasets of your choosing."
We do not yet have SPM packaged for Fedora, but it is on our list of
packages:
https://pagure.io/neuro-sig/NeuroFedora/issue/101
--
Thanks,
Regards,
Ankur Sinha "FranciscoD" (He / Him / His) | https://fedoraproject.org/wiki/User:Ankursinha
Time zone: Europe/London
Hello there
I have created a new whenisgood so that we can plan the time and the
day for our next meeting. Please click on the following link and
select your suitable time: http://whenisgood.net/neurofedora_meeting
Make sure to select your timezone appropriately.
We shall collect the results in next week and will meet at a suitable
time. Please fill in your preference by this week.
--
Thanks
Regards
Aniket Pradhan
http://home.iiitd.edu.in/~aniket17133/
Aliases: MeWjOr/major
() ascii ribbon campaign - against html e-mail
/\ www.asciiribbon.org - against proprietary attachments
Hello people!
The NeuroFedora brochure is coming around great and it would be
wonderful if you all could spare some time and provide some feedback
on it. You can have a look at the brochure here [0].
We have timeboxed the whole review to a week so that Smera can make
the necessary changes and we can start using the brochure by then.
[0]: https://pagure.io/neuro-sig/NeuroFedora/issue/301
--
Thanks
Regards
Aniket Pradhan
http://home.iiitd.edu.in/~aniket17133/
Aliases: MeWjOr/major
() ascii ribbon campaign - against html e-mail
/\ www.asciiribbon.org - against proprietary attachments